Python Data Engineer

LTM; West Virginia; Presencial; USD 110 000 - 165 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Comprehensive Medical Plan Covering

Short & Long-Term Disability

401(k) Plan with Company match

Life Insurance

Vacation Time

Sick Leave

Paid Holidays

Paid Paternity Leave

Paid Maternity Leave

Resumo da oferta

LTIMindtree is seeking a skilled Python Data Engineer to design and build scalable ETL pipelines using AWS data services. The role emphasizes data quality, validation, and robust data modeling for hierarchical and dimensional data structures.

Responsibilities include implementing schema-driven pipelines, collaborating with cross-functional teams, and integrating Databricks JDBC feeds, SageMaker endpoints, and Chronos interfaces while maintaining secure data handling practices.

Qualificações

• Experience designing and implementing ETL pipelines.
• Proficiency with Python data engineering tools (pandas, numpy).
• Strong SQL and data modeling skills for hierarchical and dimensional structures.
• Experience with AWS data services (S3, IAM, DynamoDB, SSM).
• Data validation and data quality engineering expertise.
• Familiarity with Databricks JDBC data feeds and analytics formats (Parquet, CSV).
• Version control with Git and CI/CD workflows (GitHub Actions).
• Infrastructure as code using Terraform; SageMaker/Chronos integration familiarity.

Responsabilidades

• Develop, maintain, and optimize ETL pipelines and data workflows.
• Build data models for analytics and reporting across hierarchical and dimensional datasets.
• Manage AWS data services to store, secure, and process large datasets.
• Perform data validation and quality checks to ensure integrity.
• Collaborate with cross-functional teams to integrate SQL queries and Databricks JDBC feeds.
• Work with columnar data formats for storage optimization and analytics.
• Process and analyze timeseries data; write unit/integration tests for data code.
• Use version control and automation to maintain codebase and infrastructure.
• Support machine learning endpoints integration (SageMaker and Chronos).
• Ensure secure data handling and compliance across data lifecycle.

Conhecimentos

Python

ETL pipelines

SQL

Data modeling

Data validation

Data quality

Git & GitHub Actions

Terraform

Databricks JDBC

SageMaker integration

Chronos endpoints

AWS services

Ferramentas

Databricks

JDBC

Parquet

CSV

SageMaker

Chronos

Git

Terraform

Descrição da oferta de emprego

Role Description

Job Summary

Seeking a skilled Python Data Engineer with expertise in ETL pipeline design AWS data services and data quality engineering to support scalable data solutions

Job Description

Strong proficiency in Python data engineering using pandas and numpy Design and implementation of ETLdata pipelines that are schemadriven and configurationdriven Data modeling for hierarchical and dimensional data structures Experience with AWS data services including S3 IAM DynamoDB and SSM Expertise in data validation and dataquality engineering Proficient in SQL and working with DatabricksJDBC feeds Knowledge of columnar and analytics file formats such as Parquet and CSV pragmatics Handling and processing of timeseries data Implementing testing and ensuring reproducibility for data code Familiarity with Git GitHub Actions and Terraform for version control and infrastructure as code Integration experience with SageMaker and Chronos endpoints at the interface level Ensuring secure data handling practices throughout the data lifecycle

Roles and Responsibilities

• Develop maintain and optimize ETL pipelines and data workflows following schema and configurationdriven approaches
• Build and maintain data models for hierarchical and dimensional datasets to support analytics and reporting
• Manage and utilize AWS data services to store secure and process large datasets
• Perform rigorous data validation and quality checks to ensure data integrity
• Collaborate with crossfunctional teams to integrate SQL queries and DatabricksJDBC data feeds
• Work with columnar data formats and optimize data storage and retrieval
• Handle timeseries data processing and analysis tasks
• Write unit and integration tests to guarantee reproducibility and reliability of data code
• Use version control tools and automation workflows to maintain codebase and infrastructure
• Support integration of machine learning endpoints such as SageMaker and Chronos
• Implement and enforce secure data handling and compliance standards

Other Details

Variable Compensation: This position includes a bonus or variable payout component based on individual and organizational performance. Actual compensation within the range will be dependent upon the individual's skills, experience, performance and internal equity.

Benefits/perks listed below may vary depending on the nature of your employment with LTIMindtree (“LTIM”):

Benefits And Perks

• Comprehensive Medical Plan Covering Medical, Dental, Vision
• Short Term and Long-Term Disability Coverage
• 401(k) Plan with Company match
• Life Insurance
• Vacation Time, Sick Leave, Paid Holidays
• Paid Paternity and Maternity Leave

The range displayed on each job posting reflects the minimum and maximum salary target for the position across all US locations. Within the range, individual pay is determined by work location and job level and additional factors including job-related skills, experience, and relevant education or training. Depending on the position offered, other forms of compensation may be provided as part of overall compensation like an annual performance-based bonus, sales incentive pay and other forms of bonus or variable compensation.

Disclaimer:

The compensation and benefits information provided herein is accurate as of the date of this posting.

LTIMindtree

LTIMindtree is an equal opportunity employer that is committed to diversity in the workplace. Our employment decisions are made without regard to race, color, creed, religion, sex (including pregnancy, childbirth or related medical conditions), gender identity or expression, national origin, ancestry, age, family-care status, veteran status, marital status, civil union status, domestic partnership status, military service, handicap or disability or history of handicap or disability, genetic information, atypical hereditary cellular or blood trait, union affiliation, affectional or sexual orientation or preference, or any other characteristic protected by applicable federal, state, or local law, except where such considerations are bona fide occupational qualifications permitted by law.